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检索条件"任意字段=9th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2014"

共 85 条记录，以下是41-50 订阅

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Super-resolving a Single Intensity/Range image via Non-local Means and Sparse Representation 14

Super-resolving a Single Intensity/Range Image via Non-local...

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Mandal, Srimanta Bhavsar, Arnav Sao, Anil K. School of Computing and Electrical Engineering Indian Institute of Technology Mandi HP India

ISBN: (纸本)1595930361

We propose an example-based super-resolution (SR) framework, which uses a single input image and, unlike most of the SR methods does not need an external high resolution (HR) dataset. Our SR approach is based in sparse representation framework, which depends on a dictionary, learned from the given test image across different scales. In addition, our sparse coding focuses on the detail information of the image patches. Furthermore, in the above process we have considered non-local combination of similar patches in the input image, which assist us to improve the quality of the SR result. We demonstrate the effectiveness of our approach for intensity images as well as range images. Contemplating the importance of edges in images of both these modalities, we have added an edge preserving constraint that will maintain the continuity of edge related information to the input low resolution image. We investigate the performance of our approach by rigorous experimental analysis and it shows to perform better than some state-of-the-art SR approaches. Copyright 2014 ACM.

关键词： image enhancement

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High throughput MR image reconstruction using compressed sensing 14

High throughput MR image reconstruction using compressed sen...

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Deka, Bhabesh Datta, Sumit Dept. of Electronics and Communication Engg. Tezpur University Tezpur Assam784028 India

ISBN: (纸本)1595930361

Magnetic resonance imaging (MRI) is an essential soft tissue imaging technique. Major limitation of this imaging technique is due to its slow acquisition. MR image reconstruction using the compressed sensing (CS) has mainly two research areas, one, how efficiently MRI data can be acquired and the other is how fast the reconstruction can be done without degrading the quality of the reconstructed images. From the recent study, it is observed that the TV-1 -2 model for MR image reconstruction from random under-sampled data gives the best result. In this paper, we propose a novel high throughput MR image reconstruction algorithm without compromising the quality. the experimental results show that the proposed method is quite efficient compared to the state-of-the-art MR image reconstruction techniques based on compressed sensing in terms of the cpu time and the quality of the reconstructed images. Copyright 2014 ACM.

关键词： Magnetic resonance imaging

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A flow-based interest point detector for action recognition in videos 14

A flow-based interest point detector for action recognition ...

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Yadav, Gaurav Kumar Sethi, Amit Department of Electronics and Electrical Engineering Indian Institute of Technology Guwahati781039 India

ISBN: (纸本)1595930361

Video interest points, in combination with local appearance descriptors, are used for human action recognition. Most of the previously proposed video interest point detectors are straightforward extensions of some image interest point detector or the other. these methods treat the temporal dimension (inter-frame) similar to the spatial dimensions (intra-frame). We argue that certain unique properties of the temporal dimension beg a different treatment. We propose an interest point detector based on vector calculus of optical flow to take advantage of the unique properties of the temporal dimension. Compared to previously proposed methods, the proposed method exhibits higher repeatability (robustness) and lower displacement (stability) of interest points under two common video transformations tested-video compression and spatial scaling. It also shows competitive action recognition performance when paired with appropriate feature descriptors in a bag of features model. Copyright is held by the authors.

关键词： Optical flows

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Digitization of historic inscription images using cumulants based simultaneous blind source extraction 14

Digitization of historic inscription images using cumulants ...

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Jayanthi, N. Tomar, Ayush Raj, Aman Indu, S. Chaudhury, Santanu Delhi Technological University New Delhi India Indian Institute of Technology New Delhi India

ISBN: (纸本)1595930361

In this paper a novel method to address the problem of enhancement and binarization of historic inscription images is presented. Inscription images in general have no distinction between the text layer and background layer due to absence of color difference and possess highly correlated signals and noise. the proposed technique provides a suitable method to separate the text layer from the historic inscription images by considering the problem as blind source separation which aims to calculate the independent components from a linear mixture of source signals, by maximizing a contrast function based on higher order cumulants. Further, the results are compared with existing ICA based techniques like NGFICA and Fast-ICA. Copyright 2014 ACM.

关键词： Blind source separation

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Patch flow based visual object tracking 14

Patch flow based visual object tracking

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Prabhu, Nikita Ramakanth, S. Avinash Babu, R. Venkatesh Video Analytics Lab. SERC Indian Institute of Science Bangalore India

ISBN: (纸本)1595930361

this paper proposes a novel algorithm for object tracking using Approximate Nearest Neighbour Fields (ANNF). ANNF maps have been previously used to address several problems like denoising, image completion, re-targeting and medical image analysis. In this paper, we deal with the challenging problem of visual object tracking, using patch flow. the proposed method uses FeatureMatch to find patch corre- spondence between successive frames, enabling the tracker to find the best match for the object in the next frame. Based on the flow, each patch is labeled as either foreground or background. the proportion of FG/BG/border patches contributing to each pixel determines its final label. We show that objects can be successfully tracked across videos, under challenging conditions such as scale variations, illumination changes and occlusion using the proposed technique. Copyright 2014 ACM.

关键词： Nearest neighbor search

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3D action recognition by learning sequences of poses 14

3D action recognition by learning sequences of poses

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9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Kruthiventi, Srinivas S.S. Venkatesh Babu, R. Video Analytics Lab. Supercomputer Education and Research Centre Indian Institute of Science Bangalore India

ISBN: (纸本)1595930361

Action recognition from 3D depth maps/skeleton has been an active research area in computer vision in the recent past. In this paper, we propose a method for action recognition by learning the sequence of various poses involved while performing an action. Each pose in the sequence is represented as a set of 3D edge vectors connecting important joint points in the skeleton and 3D trajectory vectors connecting the joint point locations in the previous frame with that in the current frame. the training samples of each action class, represented as sequences of poses, are time normalized using Dynamic Time Warping(DTW) and average pooled to construct the model sequence representing the action. Action recognition on a test sequence is achieved by finding its nearest model sequence in terms of a proposed distance measure. the effectiveness of the proposed algorithm is evaluated on two challenging datasets: Berkeley Multimodal Human Action Database and MSR Action 3D dataset. Copyright 2014 ACM.

关键词： Gesture recognition

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Concept level discriminant analysis techniques for dimension reduction in image classification tasks 14

Concept level discriminant analysis techniques for dimension...

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Raman, Ramya K. Sekhar, C. Chandra Department of Computer Science and Engineering Indian Institute of Technology Madras India

ISBN: (纸本)1595930361

A limitation of using the discriminant analysis techniques for dimension reduction in image classification tasks is that the number of classes is significantly smaller than the dimension of global feature vectors used to represent the images. In such cases, the reduced dimension is restricted by the number of classes and that reduced dimension may not adequately capture the necessary discriminatory information for classification. We propose a method to perform the discriminant analysis using the concept level labels for local feature vectors extracted from the blocks of an image. the dimension reduction is carried out on the local feature vectors. We consider the indices of the clusters of local feature vectors of all the images as the unnamed concept level labels. As the number of concept level labels is larger than the number of class level labels, the reduced dimension for local feature vectors can be higher than the number of class level labels. We consider the Gaussian mixture model based classifiers and support vector machine based classifiers for image classification using the set of local feature vectors representation of images. Results of experimental studies on image classification for MIT-8 and Vogel-6 image datasets demonstrate the effectiveness of proposed concept level discriminant analysis techniques for dimension reduction. Copyright 2014 ACM.

关键词： Discriminant analysis

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Statistical learning for texture characterization 14

Statistical learning for texture characterization

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Goswami, Tilottama Agarwal, Arun Rao, C.R. School of Computer and Information Sciences University of Hyderabad Hyderabad500046 India

ISBN: (纸本)1595930361

In this paper, we propose a novel method for image texture characterization. Characterization is governed by simple perceptual variations in relative orientations in terms of either no variations present or variations present as row specific, column specific or diagonal specific. this generalization is obtained by modeling the input as a whole or image blocks depending on the broader or narrow coverage respectively. Most of the texture characterization is done either keeping a specific domain (synthetic or natural images specific to a category) or is application specific (segmentation on specific benchmark dataset or image retrieval). Contrary to this, our method is not biased towards any domain or application;rather it acts as a pre-processing step for guiding towards locating both non-textural and orientation specific textural image blocks. the proposed method quantifies the texture-tonal characterization of an image or image blocks using statistical ANOVA grading system. Once the grading for abstraction is assigned for both image as a whole and also for image blocks, the decision as to which higher-level algorithms need to be implemented on which block will become easier. the proposed method can be considered to be a three stage process - progressive sampling, image partitioning in blocks, ANOVA analysis and grading. Copyright 2014 ACM.

关键词： Analysis of variance (ANOVA)

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image completion assisted by transformation domain patch approximation 14

Image completion assisted by transformation domain patch app...

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9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Ghorai, Mrinmoy Mandal, Sekhar Chanda, Bhabatosh Indian Statistical Institute 203 B. T. Road Kolkata700108 India Indian Institute of Engineering Science and Technology Shibpur India

ISBN: (纸本)1595930361

In this paper, we propose a novel image completion method using transform domain patch approximation method and kd-tree based nearest neighbor field (NNF) computation in multiscale fashion. In NNF, two important processes are initialization of image target region and candidate patch searching method. Most of the previous techniques choose random initialization with arbitrary source image pixels or garbage values. It may misguide to image completion process and allow to select the bad candidate patches. We solve the problem using higher order singular value decomposition (HOSVD). It smoothly generates information in the target region enhancing the edge sharpness which helps to complete image structure quite successfully. It also preserves texture color in the target region. To overcome the problem of patch searching, we introduce robust kd-tree search method in our patch approximation step. Our experiment and analysis shows that the proposed method can be applied to the various types of image editing tools for natural images. Copyright 2014 ACM.

关键词： Trees (mathematics)

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Distributed video coding using local rank transform 14

Distributed video coding using local rank transform

引用

9th indian conference on computer vision, graphics and image processing, icvgip 2014

作者： Mallick, Kallol Mukherjee, Jayanta Indian Institute of Technolgy Kharagpur Kharagpur India

In today9;s world, with advanced technology and easily available portable gadgets as enabler, video has become an important medium of communication. While, the standard H.264/AVC has produced extremely good results... 详细信息

ISBN: (纸本)1595930361

In today's world, with advanced technology and easily available portable gadgets as enabler, video has become an important medium of communication. While, the standard H.264/AVC has produced extremely good results, it has not been suitable for this application domain as it is computationally intensive and unsuitable for low-power resources. In distributed video coding (DVC), an encoder requires less computation than the decoder, which usually runs at sites of higher computational resources. Our approach is to find out a novel approach in DVC, to reduce encoder complexity, using local rank transform (LRT). LRT relies on the relative ordering of local intensity values for application on visual correspondence problem. Use of LRT in DVC, to the best of our knowledge, has not been reported in literature before. First, we have developed techniques for image reconstruction using LRT and then design a DVC codec using it. We show analytically and by experimental results, that, in power-rate-distortion model, LRT encoder outperforms standard encoder (LDPCA in Stanford architecture) specially in low bit rate condition. Copyright 2014 ACM.

关键词： image reconstruction

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